[ACL2015] A Dependency-Based Neural Network for Relation Classification
2017-05-19 13:04
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paper的主旨是探讨依存信息的组合：即两个实体间的最短依存树和以及附着在最短依存树上词的子树两部分信息如何糅合在一起
这种想法的来源是：最短依存树的词的向量包含了词的基本信息， 子树提供了该词在句子中作用的词义信息
RNN: 擅长处理层级结构，在本文中用于处理subtree信息
CNN: 适合flat structure， 用于处理最短依存树上的词和依存关系
RNN处理后的subtree信息用c 表示，与词向量w拼接后形成最短依存路径上词的最终信息，
这种想法的来源是：最短依存树的词的向量包含了词的基本信息， 子树提供了该词在句子中作用的词义信息
RNN: 擅长处理层级结构，在本文中用于处理subtree信息
CNN: 适合flat structure， 用于处理最短依存树上的词和依存关系
RNN处理后的subtree信息用c 表示，与词向量w拼接后形成最短依存路径上词的最终信息，
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